Diblock copolymers play an important role for the fabrication of battery materials and fuel cells. In these applications, one block provides the mechanical stability, whereas the other is conducting. The application characteristics of the material critically depend on the morphology of the multi-component material. Using large-scale simulations we investigate the non-equilibrium morphology of diblock copolymers after a quench from the disordered phase. After the initial spinodal self-assembly, the evolution becomes protracted and the morphology becomes trapped in a sequence of non-equilibrium states. In these experimentally relevant, non-equilibrium states we observe three-dimensionally percolating network structures for volume fractions, f, of the conducting component as low as f ≥ 1/4. We quantify the conductivity and tortuosity of these structures via a simple random-walk model and observe that the conductivity of the non-equilibrium structures is significantly smaller than that of the corresponding equilibrium phases. Moreover, we find large but finite-sized, fractal-like structures inside the morphology, which influence the transport properties. To explore the morphology on different scales and mitigate finite-size effects, we employ very large simulations with billions of particles using the GPU-accelarated program SOMA. Our work demonstrates the necessity of such large system sizes for the prediction of bulk transport properties in these non-equilibrium morphologies.

Large-scale simulation of nonequilibrium network phases for battery electrolytes

2019 Fall National Meeting

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